1 Department of Nutrition and Carolina Population Center, CB# 8120, University of North Carolina, Chapel Hill, NC 27599, USA

2 Department of Environmental Sciences and Engineering, University of North Carolina, and National Health and Environmental Exposures Research Laboratory, US Environmental Protection Agency Human Studies Division, Chapel Hill, NC 27599, USA

3 Department of Epidemiology and Carolina Population Center, CB# 7435, University of North Carolina, Chapel Hill, NC 27599, USA

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Neighborhood characteristics have been associated with poor maternal and child health
outcomes, yet conceptualization of potential mechanisms is still needed. Census data
have long served as proxies for area level socioeconomic influences. Unique information
captured by neighborhood inventories, mostly conducted in northern US and Canadian
urban areas, has shown important aspects of the community environment that are not
captured by the socioeconomic and demographic aggregated individual statistics of
census data. In this paper, we describe a neighborhood data collection effort tailored
to a southern urban area.

Methods

This study used data from the Pregnancy, Nutrition and Infection (PIN) prospective
cohort study to describe neighborhoods where low- and moderate-income pregnant women
reside. Women who participated in the PIN study and who resided in Raleigh, NC and
its surrounding suburbs were included (n = 703). Neighborhood attributes captured
by the inventory included litter, housing condition, road condition, and social interactions
that informed theoretical constructs of physical incivility, territoriality and social
spaces. US Housing and Population Census 2000 data at the block group level were also
assessed to identify the unique contribution of directly observed data. We hypothesize
that neighborhood environments can influence health through psychosocial mediated
pathways that lead to increased stress, or through disadvantage leading to poor neighborhood
resources, or by protective attributes through increased social control.

Results

Findings suggest that directly observed neighborhood attributes distinguished between
different types of areas in which low-income pregnant non-Hispanic white and non-Hispanic
black women lived. Theoretically informed scales of physical incivilities, territoriality
and social spaces were constructed and found to be internally consistent. Scales were
weakly associated indicating that these constructs capture distinct information about
these neighborhoods. Physical incivilities, territoriality and social spaces scales
were poorly explained by traditional census variables used to proxy neighborhood environment.

Conclusion

If neighborhoods influence health through psychosocial mediated pathways then careful
detailing of neighborhood attributes that contribute to stress or deterioration, beyond
traditional socioeconomic status, are needed. We believe that measuring physical incivility,
territoriality and social spaces as expressions of underlying issues of maintenance
and social communication make important contributes to this field.

Background

In the last two decades, research assessing neighborhood characteristics in the United
States has expanded from exclusive reliance upon administrative records such as census
data to directly observed measures. Census data, used as a proxy for neighborhood
characteristics, have been critical for identifying important associations between
socioeconomic disadvantage and a variety of adverse maternal and child outcomes such
as maternal mortality [1], birthweight [2-11], preterm birth [12-15], neural tube defect [16], and infant mortality [1,17]. Associations between poor neighborhood socioeconomic environment, as measured by
census data, and important health behaviors that may influence the course of pregnancy
were also identified such as less physical activity [18], higher fat diets [19,20] and overweight among women but not men [21,22].

While census variables might approximate a neighborhood socioeconomic context, their
utility is limited for several reasons. First, census data are available only at decennial
intervals in the US, whereas neighborhood conditions can change within the span of
a few years. Second, the exclusive use of census variables, which are produced by
aggregating individual responses to census questions, implies that the important features
of 'neighborhoods' can be captured by aggregating individual measures. This approach
ignores the important role of contextual community features including the presence
of facilities, the nature of social interactions, the quality of shared space, and
the investments in infrastructure and community life that facilitate healthful activities,
choices and interactions [23,24]. Third, while census variables continue to function as crude surrogates for neighborhood
attributes, other aspects of the neighborhood need to be measured directly to more
clearly understand pathways through which neighborhoods might influence health outcomes
[25].

The shortcomings associated with census data have led to renewed appreciation of observational
methods utilized outside the public health field and to the development of new tools
designed to directly assess characteristics of the social and physical neighborhood
environment [26-31]. Direct observation for data collection emerged largely from urban ecologic models
that described the patterns and consequences of the growth and development of cities
in the early part of the 20th century [24,32,33]. Previous research suggests direct observation can produce reliable measures of neighborhoods
and may offer specific insights into the neighborhood dynamics contributing to physical
disorder, housing condition, territoriality expressions, social disorder, human interactions
and evidence of alcohol, drug and tobacco use [34]. By selecting indicators of the probable mechanisms, directly observed data may more
accurately define the populations at risk for adverse health outcomes and can identify
the elements in this etiologic pathway that may be targeted by public policy interventions.
Further, as the health impacts of neighborhood characteristics may vary by race and
social class, we explicitly considered directly observed neighborhood attributes in
the context of explaining racial or social class health disparities [19,35].

Three gaps in the literature were identified. First, direct observation of neighborhood
attributes has mainly occurred in northern urban areas [26,28-31,36] and has yet to be conducted on urban areas of the new south; with the exception of
New Orleans [27]. The new south is a term that describes the change in the US southern states from
a largely agricultural to an urban/suburban region marked by social and economic changes,
and rapid population growth due mainly to immigration of Hispanic and Asians to the
region since the 1970s [37]. Second, research utilizing this approach, while generally collecting similar types
of information (i.e., litter, broken windows), has not been standardized across localities,
making comparison of the types of neighborhood attributes considered to influence
health outcomes difficult [38]. Third, comparison of directly observed data to other, more standard neighborhood
indicators, such as census data, has been limited.

We sought to address these research gaps by directly measuring neighborhood characteristics
in Raleigh, NC and its surrounding suburbs for the Pregnancy, Infection and Nutrition
study; a cohort study of risk factors for preterm birth. The purpose of this paper
is to 1) describe the direct observation data collection effort conducted in urban
and suburban areas representative of the new south; 2) describe neighborhoods and
assess if neighborhood attributes differ by race; 3) compare prevalence of street
segment level neighborhood attributes that comprise social and physical constructs
between Raleigh, NC and Baltimore, MD where the survey was first created; and 4) assess
the relationship between neighborhood characteristics and census variables traditionally
used to characterize neighborhood socioeconomic conditions.

Methods

Study sample

Individual data and directly observable neighborhood attributes were collected as
part of the Pregnancy, Infection, and Nutrition (PIN) cohort, a prospective study
of determinants of preterm birth [39]. Participants were recruited from four prenatal care clinics in two settings: the
University of North Carolina Residents' and Private Physicians' Obstetrics Clinics,
the Wake County Department of Human Services, and Wake Area Health Education Center
Prenatal Care Clinics. Between 1995 and 1999, 3,163 women were recruited into the
study at 24 to 29 weeks' gestation, of whom, 973 reported their last address as within
Wake County. Of these, 703 women whose addresses were within the city limits of Raleigh
and its surrounding suburbs were included. Residential addresses were geo-coded by
Geographic Data Technology (GDT), Inc., assigning latitude and longitude coordinates
and census designations. Neighborhood-level data were collected on physical attributes
such as housing condition, commercial property, and observable social interactions.
Study procedures were in accord with the ethical standards of the Institutional Review
Board of the University of North Carolina School of Medicine and Wake Medical Center.

Data collection

Individual Level

PIN participants completed a telephone interview at 26 to 31 weeks' gestation that
solicited information on sociodemographic characteristics, health behaviors, psychosocial
factors and previous as well as current medical history.

Neighborhood instrument and protocol development and data collection

The Neighborhood Attributes Inventory was modified from a street survey developed
in Baltimore, MD for a study that examined how neighborhood factors affected the cognitive
and behavioral development of preschool age children [26]. The neighborhood attributes that were collected as part of this instrument were
the indicators for social constructs related to the physical and neighborhood surroundings
that might influence a stress response or behavioral change. We collected these neighborhood
indicators because we believed these constructs were important contextual features
for pregnant women as their presence might increase stress or influence poor health
behaviors, such as decreasing physical activity, thereby affecting maternal health
and fetal growth. PIN team researchers and maternal outreach veteran home visitors,
who are lay health advisors that visit and assist pregnant women with prenatal care,
reviewed the instrument. The instrument resulted in a 39-item survey representing
four categories of neighborhood attributes: neighborhood physical conditions; social
interactions; nonresidential land use (commercial property); and public, residential
and nonresidential space (1). The survey was pilot tested during five site visits. Ten students were hired and
participated in a 30-hour training session that focused on inter-rater reliability;
consistency of rating across time, space and person. Operational definitions for each
item were established in the Neighborhood Data Collection Protocol. Inter-rater reliability
tests were conducted twice during training and three times during data collection.
Eighty-three percent agreement was achieved during training and maintained throughout
data collection among pairs of raters.

PIN women were located in 115 of 263 (44%) Wake County block groups, which formed
the sampling frame for street segment selection. Because of limited resources, a little
over twenty percent of all street segments were randomly selected within the 115 block
groups using Arcview ArcView 3.2a software (Arcview software, ESRI, 380 New York Street,
Redlands, CA 92373-8100). PIN participants' street segments were added to the sample
if they were not included among those randomly selected. A total of 2771 street segments
comprised the final sample. Block groups were of variable size; the mean number of
block group street segments was 24 (range, 6–66 street segments). Baltimore, MD, is
distinct from Raleigh, NC in that it is a northeast urban area with jobs concentrated
in the central city, has areas of concentrated poverty, and most neighborhood streets
are laid out in a grid system. In contrast, Raleigh, NC, is more typical of the new
south with a modest downtown containing government buildings, heavy suburban development,
less concentrated population density and poverty and long, meandering streets. The
average area of census block groups for Raleigh and its suburbs is 1.26 square miles
(range, 0.10 to 15.64), considerably larger than the average area of 0.1 square miles
(range, 0.02, 0.45) in Baltimore. In large part because of the non-grid street systems,
opposing streets had inconsistent beginnings and endings. Therefore, street endings
were defined as a natural break or intersection. The length of the street segments,
the larger geographical area comprising a block group and the non-continuous nature
of the street segments sampled within each block group necessitated a windshield audit,
rather than a walking survey, to rate each street segment. The raters worked in pairs,
driving each street segment up to three times between 9 am and 4 pm. Each street segment
survey took 5–10 minutes to finish. Data collection was completed in 3 months during
the summer of 2001.

Measures

Neighborhood definition

For this research, neighborhood was defined as the census block group because it represents
the smallest census unit that may approximate one's neighborhood while still providing
stable exposure estimates. Previous research in perinatal and children's health has
found the block group to be an appropriate level of analysis for similar outcomes
[3].

Neighborhood scale development

Three theoretically informed scales were constructed based largely on previous research
in Baltimore, MD: physical incivilities, territoriality and social spaces [26]. The first, signs of physical incivilities, a combination of physical disorder and
poor housing condition, are theorized to communicate decreased local social control
and may contribute to crime and further neighborhood deterioration [30]. Items comprising the physical incivilities scale included condition of housing,
yards, commercial and public spaces, vacant or burned property, litter and graffiti.
The second scale, territoriality, was comprised of indicators including fences, hedges,
decorations, and signs, which serve as physical and symbolic demarcations of residential
property, and are thought to communicate ownership and social control that lead to
protective effects against crime and adverse community events [30,31,40]. The third scale, social spaces, was modified from the play spaces scale used by
Caughy [26] to more fully capture the influence of diet, physical activity and stress on pregnancy.
Eight variables were considered: presence of people, active people, non-resident visitors
(police, service and delivery), yards, porches, parks, streets with low speed limits,
sidewalks and racial diversity. Five items factored above 0.50 and were included in
the social spaces scale: presence of people, non-resident visitors, parks, porches
and sidewalks. Unrotated principle factor analysis of a correlation matrix among items
was used to verify the underlying factor structure of the proposed latent variables
and to obtain weights for each of the scale items. The three scales were constructed
by summing the factor-weighted items.

Census variables

Scales representing physical incivilities, territoriality and social spaces were then
assessed for the extent of overlap with census variables traditionally used to estimate
neighborhood level socioeconomic disadvantage, neighborhood stability and transportation.
Sixteen 2000 US Census block group level variables were identified and assessed for
their association with neighborhood scales. Census variables representing poverty
(% below poverty, % public assistance, % female headed household with dependents),
education (% no high school), employment (% unemployed), housing (median housing value,
% with >1 person per room), occupation (% professional or management), racial composition
(% white non-Hispanic, % Black non-Hispanic, % Hispanic), residential stability (%
older than 65 years, % homes owned, % same residence since 1995), and transportation
methods (% using private transportation to get to work, % using public transportation
to get to work) were included.

Statistical methods

Counts of each street segment neighborhood attribute were calculated, and a dichotomized
indicator for presence/absence of each attribute was constructed. Block group proportions,
the number of street segments with the attribute divided by the total number of segments
rated, were calculated. In race-stratified analyses, proportions of block group attributes
were compared using t-tests to explore how neighborhood attributes varied by race.
Neighborhood scales were tested for internal reliability with Cronbach's alpha, and
with maximum likelihood tests to assess two null hypotheses: that the number of true
underlying factors is equal to zero, and that the number of true underlying factors
is greater than one using a χ2 test with p = <0.05. Spearman's correlation coefficient was used to assess association
between the three scales and to assess the association between the scales and year
2000 census variables traditionally used to characterize neighborhood socioeconomic
conditions, stability and transportation. An analysis of variance (ANOVA) was conducted
to identify what proportion of the variance in the latent constructs, as represented
by the physical incivilities, territoriality and social spaces scales, traditional
socioeconomic census variables would explain. Analyses were conducted using Stata
8.2 [41].

Results

Description of PIN participants

Among the 703 Wake County PIN participants with complete address files, 27% were non-Hispanic
white, 66% were non-Hispanic black and 7% were of other races/ethnicities. The mean
age of PIN participants was 24 years (range, 16–40 years). Sixty-two percent were
married, and 60% had a high school education or less. The mean income, as a percentage
of the poverty level was 142% poverty (range, 8–857% poverty); 79% of the sample had
incomes at or below 185% of the poverty level, the standard eligibility criteria for
the Supplemental Food Program for Women, Infants and Children (WIC). As a whole, this
sample could be characterized as a low- to middle-income population.

As a result of the economic and racial segregation of urban areas, we anticipated
non-Hispanic white and non-Hispanic black women would live in qualitatively different
neighborhoods in Raleigh, which was what we observed. Table 1 compares the mean values of selected neighborhood characteristics between non-Hispanic
white and non-Hispanic black women. Every PIN woman was assigned the prevalence of
each street level characteristic in her block-group as her neighborhood context value
for that indicator. Then the mean value among non-Hispanic white women was compared
to the mean value among non-Hispanic black women. There was a significant difference
in mean values for most of the neighborhood attributes between these two groups of
women. Non-Hispanic white women in this study were more likely to live in block groups
that had a higher proportion of street segments with only single family dwellings
(60.4 versus 50.0%) and with sidewalks (61.0 versus 49.6%), respectively; whereas
non-Hispanic black women were more likely to live in block groups with litter (63.0
versus 41.4%) and no trespassing signs (21.8 versus 11.1%), respectively (Table 1). These differences persisted despite the PIN sample comprising mostly low-income
women of both races.

Table 1. Selected neighborhood attributes, range, mean and standard deviation for total sample
and by race

The neighborhood attribute data suggest that Raleigh NC, a city of the new urban south,
may differ from the Baltimore, MD, our urban northeast example, in important ways.
Items measuring physical incivilities, including graffiti, moderate/considerable litter,
vacant/burned properties, poorly maintained yards, housing, and public spaces, were
strikingly less prevalent in Raleigh than in Baltimore (e.g., 4% compared to 31% vacant
residence, respectively) (Table 2). These findings suggest that there were fewer overt physical signs of incivilities
in Raleigh, NC, or that incivilities might be manifested in other ways. Items measuring
territoriality, including neighborhood watch, no trespassing and security warning
signs, reaction of residents to raters, presence of borders and decorations, had similar
prevalence rates for Raleigh and Baltimore. These findings suggest that residents
of the new urban south and the urban northeast may mark their residential spaces similarly.

The Cronbach's alpha coefficient for the physical incivility scale was 0.81, for social
spaces was 0.61 and that for territoriality was 0.56 suggesting high and moderate
internal reliability of the scales. The three scales appeared to represent unique
latent constructs, as assessed by significant chi-square statistics (alpha = 0.05)
which for each scale rejected both the null hypothesis that the number of true underlying
factors is exactly zero, as well as the null hypothesis that the number of true underlying
factors is greater than one. Therefore, we used the items that represented the scales
previously published [26]. The scales were weakly correlated, the correlation between physical incivilities
and territoriality was ρ = -0.05, between physical incivilities and social spaces
was ρ = 0.39, and between territoriality and social spaces was ρ = -0.03, indicating
the scales represent distinct latent constructs.

Association of scales with 2000 US Census variables

Presented in Table 3 are the Spearman's correlation coefficients between the scales for physical incivilities,
territoriality and social spaces, and 16 block group level census variables. Correlations
between the physical incivilities scale and census variables ranged between 0.16 (%
same residence since 1995) and 0.68 (% no high school education). Generally, the physical
incivilities scale was moderately and positively associated with non-Hispanic black
race, poverty, and low education, and negatively associated with non-Hispanic white
race, professional occupation and housing value (ρ ≥ 0.5). Census variables representing
proportion elderly and Hispanic residents, employment status, housing, residential
stability and transportation were not highly correlated with physical incivilities.
We did not anticipate high or moderate correlations (ρ ≥ 0.5) between socioeconomic
census variables and territoriality. There were weak correlations between the territoriality
scale and socioeconomic census variables ranging from 0.00 (% female headed households
with dependents) to 0.22 (% below poverty), moderate correlations with census variables
that are used to represent residential stability, from 0.45 (% older than 65 years)
to 0.58 (% same residence since 1995), and weak correlations with transportation variables.
Lastly, we correlated census variables with social spaces and hypothesized that few
would be associated with social spaces above ρ = 0.50, and that census measures of
public and private transportation use might have higher association with social spaces
than census variables used to capture socioeconomic status or residential stability.
Correlations between social spaces and socioeconomic variables ranged from 0.05 (%
Hispanic) to 0.43 (% poverty), from 0.01 (% older than 65 years) to -0.43 (% homes
owned) for residential stability, and were moderately correlated with transportation.

Table 3. Spearman's correlation coefficient among three scales and 16 census variables at the
block group level

Variance in the scales explained by traditional census variables used to capture neighborhood
disadvantage, residential stability and transportation was assessed using ANOVA [2,3,5,12]. First, the proportion of variance in physical incivility explained by poverty alone,
the most commonly used census variable to account for neighborhood disadvantage was
56%. Census variables correlated above 0.5 with physical incivilities were then assessed.
Adding to census tract poverty was % no high school, median housing value, % professional
or management occupation, and % non-Hispanic black which together explained 62% of
the variance in the physical incivilities construct. Three census variables modestly
correlated at 0.4 or greater with the territoriality scale – % same residence since
1995, % older than 65 years and % of homes owned – were used to assess and only explained
40% of the variance in the territoriality construct. Three census variables modestly
correlated at 0.4 or greater with the social spaces scale – % poverty, % of homes
owned, and % private transportation to get to work – were used to assess and only
explained 41% of the variance in the social spaces construct. The finding of moderate
to high internal reliability based on the Cronbach's alpha and that census variables
capture 62%, 40% and 41% of the physical incivilities, territoriality and social spaces
scales, respectively, suggest the scales depict unique information about these neighborhoods,
not obtainable using traditional census measures.

Discussion

This research sought to describe the neighborhood environment of Raleigh, NC, a city
of the new urban south, as part of a cohort study of risk factors for adverse pregnancy
outcomes. The new south is rapidly growing and may experience neighborhood changes
in resources and maintenance that may be important to capture through direct observation.
Conducting a windshield tour of Raleigh, NC and surrounding suburbs was necessary
because of the large geography and low population density. Although direct observation
data were collected via driving, we found we were able to use a data collection instrument
previously used in Baltimore, MD to capture neighborhood attributes.

The second objective of this paper was to analyze race-stratified neighborhood attributes,
indicating that, within the PIN sample, low-income non-Hispanic white and non-Hispanic
black women live in qualitatively distinct neighborhoods. We found that non-Hispanic
white women lived in neighborhoods with more amenities such as sidewalks, whereas
non-Hispanic black women lived in neighborhoods characterized by more markers of incivilities.
Based on theories of psychosocial etiology for adverse reproductive outcomes [42,43], these very different environments may have important effects on racial disparities
in preterm birth, a profound health disparity in the US, especially in the US south.

This particular neighborhood observation tool was chosen because the three theoretically
informed constructs of physical incivilities, territoriality and social spaces are
hypothesized to influence intermediate health outcomes during pregnancy such as stress
level, diet, physical activity and weight status, as well as delivery outcomes of
birthweight and preterm birth. Physical incivilities, characterized by poor housing,
litter and abandoned houses, may directly and indirectly influence stress by increasing
allostatic load or by influencing behaviors that help maintain low stress levels.
Feelings of being unsafe might influence psychologically mediated pathways increasing
stress and a physiological response to stress that over time increases a woman's allostatic
load [44]. This chronic stress condition has been presented as a weathering effect that over
time influences poor health outcomes [45]. Signs of physical incivilities that increased stress and decrease perceived safety
may influence behavioral changes [46] such as the inability to exercise in one's own neighborhood [18] or increased gonorrhea rates [27]. Conversely, territoriality is thought to communicate social control and have a protective
affect on health, perhaps lowering allostatic load or increasing confidence to walk
within one's neighborhood. The social spaces construct is hypothesized to promote
personal interaction thereby increasing opportunities for social control and activity
within one's neighborhood. To the extent that stress mediated pathways are involved
in health outcomes, this neighborhood survey may be applicable for the study of other
health outcomes such as weight status or chronic diseases.

Our research also sought to compare the attributes of a Raleigh, NC and its suburbs,
a city of the new urban south, with those of Baltimore MD, a city with characteristics
of the northern urban industrial center. Contrasting neighborhood attributes from
various geographies is important because regardless of different developmental histories,
similarities in neighborhood physical and observable manifestations that persist may
help us understand how neighborhoods are important to health [38]. Despite the scarcity of items representing incivilities in the Raleigh area, the
physical incivilities scales had high internally reliability based on Cronbach's alpha
scores, and territoriality and social spaces had moderate internal reliability. The
low correlation estimates among the scales suggested that the scales captured distinct
constructs and provided unique information about neighborhood attributes. We hypothesize
that physical incivilities, territoriality and social spaces are importantly associated
with reproductive health outcomes in Raleigh, NC and its surrounding suburbs, largely
through psychosocially mediated pathways [42].

The fourth objective of this paper was to demonstrate that the unique neighborhood
information obtained through direct observation is distinct from that of traditionally
used census data. While the markers for incivilities, territoriality and social spaces
may be used to estimate neighborhood deterioration, upkeep or resident investment,
census variables can not replicate the information provided by these scales. Further,
the theoretically informed scales suggest a mechanism regarding how neighborhoods
can influence health outcomes. The inadequacy of using poverty as a surrogate for
neighborhood dynamics is due to heterogeneity across low-income neighborhoods with
regards to disadvantage, crime, and resources, as has been observed in previous studies
[47]. In a study of neighborhood effects on gonorrhea rates in New Orleans, LA, Cohen
et al. found that a "Broken Windows" index – a directly observed measure combining
housing condition, graffiti, accumulated garbage, abandoned vehicles and public high
schools with problems – distinguished among low-income neighborhoods [27]. Low-income, low broken windows indexed neighborhoods had significantly lower gonorrhea
rates than low-income, high broken windows indexed neighborhoods. These illustrations
show the importance of using directly observed data in combination with census or
other administrative data; geo-referenced data such as parks, commerce, schools, zoning,
alcohol outlets, and crime data [27,47]; and perceived neighborhood environment data [48], to provide a rich picture of neighborhoods and their attributes, with minimal investment
of time and expense, and to better understand mechanisms of neighborhood influences
on health. In addition, increased accessibility to geocoded data has enabled more
sophisticated modeling techniques and permit exposures to be characterized as simple
counts or as rates for various units of geographic analysis [49,50]. Geocoding allows one to observe the spatial distribution of an exposure over multiple
geographies to identify hot spots, assess spatial autocorrelation, and allows the
creation of accessibility measures and geo-simulation [51]. The utility of different modeling techniques permits exploration of the most relevant
exposure classification for health outcomes. In this way not only can the relationship
of geography be better understood but the influence of changes in terrain on health
can be assessed enabling researcher to explore causal mechanisms and move beyond simple
associations.

Although newly developed southern US cities are notably less segregated than the industrial
centers of the northeast [52], and patterns of poverty and neighborhood development are different because of the
growth of these areas in an era since the demise of heavy industry as the basis for
economic organization [53], the recent establishment of these communities may provide fewer social resources
that could help to buffer effects of harmful environments. Furthermore, cities in
which major growth has occurred since the automobile became ubiquitous are more geographically
dispersed and may reduce easy access to facilities and amenities compared to cities
with concentrated population centers and long-established urban transit systems. Reduced
service concentration may be especially burdensome for poor individuals and families
who may not own a car or have hours to devote to traveling between service facilities.
Furthermore, recent growth in new south centers such as Raleigh, Charlotte and Atlanta
has occurred since the era of suburban flight, meaning that center-city areas were
never abandoned, since the center city never gained prominence in this later era.
This implies a lower prevalence of the 'incivilities' that emerge when populations
abandon decaying areas of the city for opportunities in newer suburbs. Yet, even with
the lower prevalence of incivilities, their existence may influence health outcomes,
and as population growth and development occurs, incivilities in poorly maintained
neighborhoods may increase.

Future research is needed to corroborate data collection methods and findings. Directly
observed neighborhood attributes can be combined with geographic information systems
and resource inventories to validate findings, and can be augmented by these sources
and census data to provide a detailed contextual database for the analysis of neighborhoods'
influences on health outcomes. Longitudinal data collection and analysis of individuals
and the neighborhoods in which they reside will be important as we move forward with
this research. Analysis using the physical incivilities, territoriality and social
spaces scales to predict health outcomes, particularly adverse birth outcomes is needed
and forthcoming.

Authors' contributions

BAL was involved in the study design, implementation, data analysis, execution and
writing up of the draft and final copies of the manuscript. LM was involved with the
implementation, data entry, data analysis, and preparation of the manuscript. JSK
was involved in the study design, interpretation of results and preparation of the
manuscript. ND conceived the need for the study, was involved in the study design
and preparation of the manuscript. MC assisted with the interpretation of the findings
and was involved with the preparation of the manuscript. POC served as a consultant
for the project, was involved with the interpretation of the findings and preparation
of the manuscript. DAS conceived the need for the study, was involved in the study
design and preparation of the manuscript.

Acknowledgements

We could not have carried out this data collection effort without the greatly appreciated
work and assistance of the Carolina Population Center's Spatial Analysis Unit and
by James Terry. We greatly appreciate the cooperation and support of all study staff
members, prenatal care providers, and particularly the women who participated in this
study. This study was supported by the cooperative agreement ASPH/CDC project S1099-19/21
"Community-level Social Influences on Preterm Birth"; and by grants HD28684 and HD28684A
from the National Institute of Child Health and Human Development, National Institutes
of Health; funding from the National Institutes of Health, General Clinical Research
Centers program of the Division of Research Resources (grant # RR00046); cooperative
agreements S455/16-17 through the Association of Schools of Public Health/Centers
for Disease Control and Prevention, and U64/CCU412273 through the Centers for Disease
Control and Prevention; and funds from the Wake Area Health Education Center in Raleigh,
North Carolina.

Herrick H: The association of poverty and residence in predominantly black neighborhoods with
the occurrence of preterm births among black women: a case-control study of three
North Carolina metropolitan areas. Raleigh, North Carolina: The State Center for Health and Environmental Statistics; 1996:1-12.

Shaw C, McKay H: Juvenile Delinquency and Urban Areas: A Study of the Rates of Delinquents in Relation
to Differential Characteristics of Local Communities in American Cities. Chicago, IL: University of Chicago Press; 1942.